Journal cover Journal topic
Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 3.400 IF 3.400
  • IF 5-year value: 3.841 IF 5-year
    3.841
  • CiteScore value: 3.71 CiteScore
    3.71
  • SNIP value: 1.472 SNIP 1.472
  • IPP value: 3.57 IPP 3.57
  • SJR value: 1.770 SJR 1.770
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 70 Scimago H
    index 70
  • h5-index value: 49 h5-index 49
AMT | Articles | Volume 12, issue 3
Atmos. Meas. Tech., 12, 1673–1683, 2019
https://doi.org/10.5194/amt-12-1673-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue: Layered phenomena in the mesopause region (ACP/AMT inter-journal...

Atmos. Meas. Tech., 12, 1673–1683, 2019
https://doi.org/10.5194/amt-12-1673-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 15 Mar 2019

Research article | 15 Mar 2019

A new method of inferring the size, number density, and charge of mesospheric dust from its in situ collection by the DUSTY probe

Ove Havnes et al.
Related authors  
Multi-scale measurements of mesospheric aerosols and electrons during the MAXIDUSTY campaign
Tarjei Antonsen, Ove Havnes, and Andres Spicher
Atmos. Meas. Tech., 12, 2139–2153, https://doi.org/10.5194/amt-12-2139-2019,https://doi.org/10.5194/amt-12-2139-2019, 2019
Short summary
A comparison of overshoot modelling with observations of polar mesospheric summer echoes at radar frequencies of 56 and 224 MHz
O. Havnes, H. Pinedo, C. La Hoz, A. Senior, T. W. Hartquist, M. T. Rietveld, and M. J. Kosch
Ann. Geophys., 33, 737–747, https://doi.org/10.5194/angeo-33-737-2015,https://doi.org/10.5194/angeo-33-737-2015, 2015
Short summary
Related subject area  
Subject: Aerosols | Technique: In Situ Measurement | Topic: Data Processing and Information Retrieval
Gaussian process regression model for dynamically calibrating and surveilling a wireless low-cost particulate matter sensor network in Delhi
Tongshu Zheng, Michael H. Bergin, Ronak Sutaria, Sachchida N. Tripathi, Robert Caldow, and David E. Carlson
Atmos. Meas. Tech., 12, 5161–5181, https://doi.org/10.5194/amt-12-5161-2019,https://doi.org/10.5194/amt-12-5161-2019, 2019
Short summary
Methods for identifying aged ship plumes and estimating contribution to aerosol exposure downwind of shipping lanes
Stina Ausmeel, Axel Eriksson, Erik Ahlberg, and Adam Kristensson
Atmos. Meas. Tech., 12, 4479–4493, https://doi.org/10.5194/amt-12-4479-2019,https://doi.org/10.5194/amt-12-4479-2019, 2019
Short summary
Automatic pollen recognition with the Rapid-E particle counter: the first-level procedure, experience and next steps
Ingrida Šaulienė, Laura Šukienė, Gintautas Daunys, Gediminas Valiulis, Lukas Vaitkevičius, Predrag Matavulj, Sanja Brdar, Marko Panic, Branko Sikoparija, Bernard Clot, Benoît Crouzy, and Mikhail Sofiev
Atmos. Meas. Tech., 12, 3435–3452, https://doi.org/10.5194/amt-12-3435-2019,https://doi.org/10.5194/amt-12-3435-2019, 2019
Short summary
An open platform for Aerosol InfraRed Spectroscopy analysis – AIRSpec
Matteo Reggente, Rudolf Höhn, and Satoshi Takahama
Atmos. Meas. Tech., 12, 2313–2329, https://doi.org/10.5194/amt-12-2313-2019,https://doi.org/10.5194/amt-12-2313-2019, 2019
Short summary
Understanding atmospheric aerosol particles with improved particle identification and quantification by single-particle mass spectrometry
Xiaoli Shen, Harald Saathoff, Wei Huang, Claudia Mohr, Ramakrishna Ramisetty, and Thomas Leisner
Atmos. Meas. Tech., 12, 2219–2240, https://doi.org/10.5194/amt-12-2219-2019,https://doi.org/10.5194/amt-12-2219-2019, 2019
Short summary
Cited articles  
Amyx, K., Sternovsky, Z., Knappmiller, S., Robertson, S., Horányi, M., and Gumbel, J.: In-situ measurement of smoke particles in the wintertime polar mesosphere between 80 and 85 km altitude, J. Atmos. Sol.-Terr. Phy., 70, 61–70, 2008. 
Antonsen, T. and Havnes, O.: On the detection of mesospheric meteoric smoke particles embedded in noctilucent cloud particles with rocket-borne dust probes, Rev. Sci. Instrum., 86, 033305, https://doi.org/10.1063/1.4914394, 2015. 
Antonsen, T., Havnes, O., and Mann, I.: Estimates of the Size Distribution of Meteoric Smoke Particles From Rocket-Borne Impact Probes, J. Geophys. Res, 122, 12353–12365, https://doi.org/10.1002/2017JD027220, 2017. 
Asmus, H., Robertson, S., Dickson, S., Friedrich, M., and Megner, L.: Charge balance for the mesosphere with meteoric dust particles, J. Atmos. Sol.-Terr. Phy., 127, 137–149, https://doi.org/10.1016/j.jastp.2014.07.010, 2015. 
Backhouse, T. W.: The luminous cirrus cloud of June and July, Meteorol. Mag., 20, 133, 1885. 
Publications Copernicus
Download
Short summary
We present a new method of analyzing data from rocket-borne aerosol detectors of the Faraday cup type (DUSTY). By using models for how aerosols are charged in the mesosphere and how they interact in a collision with the probes, fundamental parameters like aerosol radius, charge, and number density can be derived. The resolution can be down to ~ 10 cm, which is much lower than other available methods. The theory is furthermore used to analyze DUSTY data from the 2016 rocket campaign MAXIDUSTY.
We present a new method of analyzing data from rocket-borne aerosol detectors of the Faraday cup...
Citation